Channel Selection Information Hiding Scheme for Tracking User Attack in Cognitive Radio Networks

For the discontinuous occupancy of primary users in cognitive radio networks(CRN),the time-varying of spectrum holes becomes more and more highlighted.In the dynamic environment,cognitive users can access channels that are not occupied by primary users,but they have to hand off to other spectrum holes to continue communication when primary users come back,which brings new security problems.Tracking user attack(TUA) is a typical attack during spectrum handoff,which will invalidate handoff by preventing user accessing,and break down the whole network.In this paper,we propose a Channel Selection Information Hiding scheme(CSIH) to defense TUA.With the proposed scheme,we can destroy the routes to the root node of the attack tree by hiding the information of channel selection and enhance the security of cognitive radio networks.

Generating IDS Attack Pattern Automatically Based on Attack Tree

Generating attack pattern automatically based on attack tree is studied. The extending definition of attack tree is proposed. And the algorithm of generating attack tree is presented. The method of generating attack pattern automatically based on attack tree is shown, which is tested by concrete attack instances. The results show that the algorithm is effective and efficient. In doing so, the efficiency of generating attack pattern is improved and the attack trees can be reused.

Threat Modeling-Oriented Attack Path Evaluating Algorithm

In order to evaluate all attack paths in a threat tree,based on threat modeling theory,a weight distribution algorithm of the root node in a threat tree is designed,which computes threat coefficients of leaf nodes in two ways including threat occurring possibility and the degree of damage.Besides,an algorithm of searching attack path was also obtained in accordence with its definition.Finally,an attack path evaluation system was implemented which can output the threat coefficients of the leaf nodes in a target threat tree,the weight distribution information,and the attack paths.An example threat tree is given to verify the effectiveness of the algorithms.

An Improved Model of Attack Probability Prediction System

This paper presents a novel probability generation algorithm to predict attacks from an insider who exploits known system vulnerabilities through executing authorized operations. It is different from most intrusion detection systems （IDSs） because these IDSs are inefficient to resolve threat from authorized insiders. To deter cracker activities, this paper introduces an improved structure of augmented attack tree and a notion of ＂minimal attack tree＂, and proposes a new generation algorithm of minimal attack tree. We can provide a quantitative approach to help system administrators make sound decision.

Security-Critical Components Recognition Algorithm for Complex Heterogeneous Information Systems

With the skyrocketing development of technologies,there are many issues in information security quantitative evaluation(ISQE)of complex heterogeneous information systems(CHISs).The development of CHIS calls for an ISQE model based on security-critical components to improve the efficiency of system security evaluation urgently.In this paper,we summarize the implication of critical components in different filed and propose a recognition algorithm of security-critical components based on threat attack tree to support the ISQE process.The evaluation model establishes a framework for ISQE of CHISs that are updated iteratively.Firstly,with the support of asset identification and topology data,we sort the security importance of each asset based on the threat attack tree and obtain the security-critical components(set)of the CHIS.Then,we build the evaluation indicator tree of the evaluation target and propose an ISQE algorithm based on the coefficient of variation to calculate the security quality value of the CHIS.Moreover,we present a novel indicator measurement uncertainty aiming to better supervise the performance of the proposed model.Simulation results show the advantages of the proposed algorithm in the evaluation of CHISs.

A Systematic Risk Assessment Framework of Automotive Cybersecurity

The increasingly intelligent and connected vehicles have brought many unprecedented automotive cybersecurity threats,which may cause privacy breaches,personal injuries,and even national security issues.Before providing effective security solutions,a comprehensive risk assessment of the automotive cybersecurity must be carried out.A systematic cybersecurity risk assessment framework for automobiles is proposed in this study.It consists of an assessment process and systematic assessment methods considering the changes of threat environment,evaluation target,and available information in vehicle lifecycle.In the process of risk identification and risk analysis,the impact level and attack feasibility level are assessed based on the STRIDE model and attack tree method.An automotive cybersecurity risk matrix using a global rating algorithm is then constructed to create a quantitative risk metric.Finally,the applicability and feasibility of the proposed risk assessment framework are demonstrated through a use case,and the results prove that the proposed framework is effective.The proposed assessment framework helps to systematically derive automotive cybersecurity requirements.